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Agent Skill · 研究检索

academic-writing-refiner(学术写作精炼者)

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

academic-writing-refiner 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,674 个 Skill 里排第 53,999。

总安装 517周安装 22GitHub Stars 209下载 181核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:academic-writing-refiner(学术写作精炼者)
来源仓库:https://github.com/wentorai/research-plugins
仓库路径:skills/academic-writing-refiner
安装命令:
npx skills add https://github.com/wentorai/research-plugins --skill academic-writing-refiner
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/wentorai/research-plugins --skill academic-writing-refiner

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

学术写作精炼者用于辅助文档、README、Markdown 等内容的整理与改写,提升文本可读性。它适合提炼结构、补齐章节、统一术语或检查链接,适用于内容稿件优化场景。通过 npx skills add 命令从指定仓库安装,需保留项目已有事实和路径。涉及对外文案时应控制语气,避免过度营销或夸大能力。

academic-writing-refiner 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/academic-writing-refiner

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/wentorai/research-plugins --skill academic-wri…;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

academic-writing-refiner 怎么安装?

在终端执行 npx skills add https://github.com/wentorai/research-plugins --skill academic-writing-refin…。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

academic-writing-refiner 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

academic-writing-refiner 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

academic-writing-refiner 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

academic-writing-refiner 用的人多吗?

公开数据是累计安装 517 次,近一周安装 22 次,下载 181 次,GitHub 209 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

academic-writing-refiner 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
academic-writing-refiner

学术写作精炼者 · 本页

517209需要联网未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Academic Writing Refiner

Overview

Academic papers are judged not only on their scientific merit but also on the quality of their English. Grammatical errors, awkward phrasing, and non-native patterns (commonly called "Chinglish" when originating from Chinese-English interference) can distract reviewers and undermine credibility.

This skill provides a systematic checklist for identifying and correcting common academic English issues. It draws from the academic-writing-guide repository (327+ stars) maintained by SYSUSELab, which catalogs frequent mistakes observed in student and researcher manuscripts across STEM disciplines.

The approach is checklist-driven: rather than relying solely on automated tools, researchers learn to recognize error patterns and self-edit effectively. This skill is especially useful for non-native English speakers preparing manuscripts for international journals and conferences.

Common Error Categories

Grammar and Syntax Errors

Error TypeExample (Wrong)Correction
Article misuse"We propose a novel the method""We propose a novel method"
Subject-verb disagreement"The results shows that...""The results show that..."
Tense inconsistency"We train the model and evaluated it""We trained the model and evaluated it"
Dangling modifier"Using gradient descent, the loss decreased""Using gradient descent, we decreased the loss"
Run-on sentence"The model converges fast it achieves high accuracy""The model converges fast and achieves high accuracy"

Chinglish Patterns

These are interference patterns common when translating from Chinese thought patterns into English:

  1. Topic-comment structure. Chinese allows "As for X, Y does Z." English prefers "Y does Z to X."

- Wrong: "As for the dataset, we use ImageNet." - Better: "We use ImageNet as our dataset."

  1. Redundant verbs. Chinese often uses verb-verb compounds that become redundant in English.

- Wrong: "We can be able to achieve..." - Better: "We can achieve..."

  1. Missing determiners. Chinese has no articles, leading to dropped "the/a/an."

- Wrong: "Model achieves state-of-art result." - Better: "The model achieves a state-of-the-art result."

  1. Overuse of "respectively."

- Wrong: "The accuracy and F1 are 95% and 0.93 respectively." - Better: "The accuracy is 95% and the F1 score is 0.93."

  1. "With the development of..." This opening is overused to the point of cliche.

- Better: Lead with the specific problem or finding.

Self-Editing Checklist

Apply this checklist before submitting any manuscript:

Pass 1: Structure and Flow

  • Each paragraph has a clear topic sentence.
  • Transitions connect paragraphs logically (however, therefore, in contrast).
  • No paragraph exceeds 200 words.
  • Figures and tables are referenced in order.

Pass 2: Grammar and Mechanics

  • All verbs agree with their subjects.
  • Tense is consistent within each section (past for Methods/Results, present for general truths).
  • Every acronym is defined on first use.
  • No comma splices or run-on sentences.
  • Articles (a, an, the) are used correctly.

Pass 3: Style and Conciseness

  • Remove "very," "really," "quite," "basically" unless essential.
  • Replace "in order to" with "to."
  • Replace "a large number of" with "many" or give the exact count.
  • Convert passive voice to active where possible.
  • Eliminate "it is well known that" and similar filler phrases.

Pass 4: Technical Accuracy

  • All numbers have units.
  • Table column headers are unambiguous.
  • Equations are numbered and referenced.
  • Statistical claims include confidence intervals or p-values.

Automated Polishing Tools

While manual review is irreplaceable, these tools serve as a useful second pass:

# LanguageTool CLI for grammar checking
java -jar languagetool-commandline.jar -l en-US paper.tex

# Writefull for academic-specific suggestions (VS Code extension)
# Install from VS Code marketplace: "Writefull for LaTeX"

# textlint for rule-based prose linting
npm install -g textlint textlint-rule-no-dead-link textlint-rule-write-good
textlint paper.md

Tool Comparison

ToolTypeAcademic FocusFree Tier
GrammarlyCloudGeneral + academicYes (limited)
WritefullPluginHigh (trained on papers)Yes
LanguageToolLocal/CloudGeneralYes (full)
textlintCLIConfigurable rulesYes (open source)
TrinkaCloudHigh (academic-specific)Yes (limited)

Sentence-Level Revision Examples

Before and After

Before: "In recent years, with the rapid development of deep learning, more and more researchers have paid attention to the problem of image classification, which is a very important task in computer vision."

After: "Image classification is a fundamental task in computer vision. Recent advances in deep learning have renewed interest in this problem, with convolutional and transformer architectures achieving human-level accuracy on standard benchmarks."

Before: "We can observe from Table 1 that our method can achieve better performance than baseline methods in terms of all evaluation metrics."

After: "Our method outperforms all baselines across every metric (Table 1)."

Best Practices

  • Read published papers in your target venue. Absorb the register and conventions of journals like Nature, IEEE TPAMI, or ACL.
  • Have a native speaker review critical sections. At minimum, ask someone to read the Abstract and Introduction.
  • Use consistent terminology. If you call it "feature extraction" in Section 2, do not switch to "representation learning" in Section 4 unless you define the distinction.
  • Limit sentences to 25 words on average. Long sentences are harder to parse, especially for non-native readers.
  • Revise in separate passes. Do not try to fix grammar, structure, and style simultaneously.

References

平台分布

Codex

38.73%
按下载量换算70

Claude

30.29%
按下载量换算55

Cursor

20.29%
按下载量换算37

Gemini CLI

8.43%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。目前只有一个公开来源,建议同时核对源仓库。

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